Why is the last layer in resnet101 need dilation=6 ?

[andyhahaha]

I read the R-FCN paper.

After the Resnet101 they append a randomly initialized 1024-d 1x1 convolution layer to reducing dimension. However, your implementation append the a 1024-d "3x3" dilation="6" convolution layer. The paper doesn't discuss this difference. I wondering if I use 1024-d 1x1 convolution layer like R-FCN, whether the result will be different or not?

Thx for your help !

[liurongdev]

I read the R-FCN paper.

After the Resnet101 they append a randomly initialized 1024-d 1x1 convolution layer to reducing dimension. However, your implementation append the a 1024-d "3x3" dilation="6" convolution layer. The paper doesn't discuss this difference. I wondering if I use 1024-d 1x1 convolution layer like R-FCN, whether the result will be different or not?

Thx for your help ! Can you add qq private chat? 1069919773